Developing applications that implement TM Forum (TMF) Open APIs can be greatly accelerated with the help of GitHub Copilot, an AI-based coding assistant. By combining Copilot’s code-generation capabilities with TMF’s standardized API specifications, developers can speed up coding while adhering to industry standards. In this blog post, we’ll walk through how to set up a project with GitHub Copilot to write TMF Open API-based applications, including prerequisites, configuration steps, an example workflow for building an API, best practices, and additional tips.
Introduction: GitHub Copilot and TM Forum Open APIs
GitHub Copilot is an AI-powered coding assistant developed by GitHub and OpenAI. It integrates with popular editors (VS Code, Visual Studio, JetBrains IDEs, etc.) and uses advanced language models to autocomplete code and even generate entire functions based on context and natural language prompts. For example, Copilot can turn a comment like “// fetch customer by ID” into a code snippet that implements that logic. It was first introduced in 2021 and is available via subscription for developers and enterprises. Copilot has the ability to interpret the code and comments in your current file and suggest code that fits, essentially acting as an AI pair programmer.
TMF Open APIs refers to a set of standardized REST APIs for telecom and digital service providers. The APIs are designed to enable seamless connectivity and interoperability across complex service ecosystems. In practice, the TMF Open API program has defined over 100 RESTful interface specifications covering various domains (such as customer management, product catalog, billing, etc.). These APIs share a common design guideline (TMF630) and data model, ensuring that services can be managed end-to-end in a consistent way.
Why use GitHub Copilot for TMF Open API development?
Integrating Copilot with TMF Open API streamlines telecom app development. Copilot helps generate boilerplate code, suggests API handling snippets, and provides usage examples, all in line with TMF specs. For developers building services like Customer Management or Product Catalog, Copilot autocompletes endpoints, models, and business logic based on learned standards, maintaining TMF consistency. Developers review and edit outputs, but Copilot eases repetitive tasks. The following sections will guide you on setup and practical use with TMF Open API.
"With GitHub Copilot, TM Forum members can accelerate API development — reducing boilerplate coding, improving consistency with our Open API standards, and freeing developers to focus on innovation rather than routine tasks. We’d love to hear from members already experimenting with Copilot — your experiences, lessons, and best practices will help shape how we embed AI-assisted coding into the wider TM Forum Open API community."
- Ian Holloway, Chief Architect, TM Forum
Prerequisites for Setting Up the Project
Before configuring GitHub Copilot in your project, make sure you have the following prerequisites in place:
- GitHub Copilot Access: You will need an active GitHub Copilot subscription or trial linked to your GitHub account. Copilot is a paid service (with a free trial for new users), so ensure your account is signed up for Copilot access. If you haven’t done this, go to the https://github.com/features/copilot and activate your subscription or trial.
- Supported IDE or Code Editor: Copilot works with several development environments. For the best experience, use a supported editor such as Visual Studio Code, Visual Studio 2022, Neovim, or JetBrains IDEs (like IntelliJ, PyCharm, etc)
- GitHub Account: Obviously, you need a GitHub account to use Copilot (since you must sign in to authorize the Copilot plugin). Ensure you have your GitHub credentials handy.
- Programming Language Environment: Set up the programming language/framework you plan to use for your TMF Open API application. Copilot supports a wide range of languages, including JavaScript/TypeScript, Python, Java, C#, etc., so choose one that suits your project.
- TMF Open API Specification: Obtain the TMF Open API specifications or documentation for the APIs you plan to implement. TM Forum provides downloadable Open API (Swagger) specs for each API (for example, the Customer Management API, Product Catalog API, etc.).
- Basic Domain Knowledge: While not strictly required, it helps to have a basic understanding of the TMF Open API domain you're working with. For example, know what “Customer Management API” or “Product Catalog API” is supposed to do at a high level (reading the TMF user guide can help). This will make it easier to prompt Copilot effectively and to validate its suggestions. For more training, please refer to the TM Forum Education Programs.
With these prerequisites met, you’re ready to configure GitHub Copilot in your development environment and integrate it into your project workflow.
Step-by-Step Guide: Configuring GitHub Copilot in Your IDE
Setting up GitHub Copilot for your project is a one-time process. Here is a step-by-step guide using Visual Studio Code as the example IDE:
Step 1: Install the GitHub Copilot Extension. Open Visual Studio Code and navigate to the Extensions view (you can click the Extensions icon on the left toolbar or press Ctrl+Shift+X on Windows / Cmd+Shift+X on Mac). In the Extensions marketplace search bar, type “GitHub Copilot”. You should see the GitHub Copilot extension by GitHub. Click Install to add it to VS Code. This will download and enable the Copilot plugin in your editor.
Step 2: Authenticate with GitHub. After installation, Copilot will prompt you to sign in to GitHub to authorize the extension. Click “Sign in with GitHub”. Log in with your GitHub credentials and grant permission to the Copilot extension.
Step 3: Enable Copilot in your Workspace/Project. Now that Copilot is installed and linked to your account, you should ensure it’s enabled for your current project. In VS Code, open the command palette (Ctrl+Shift+P / Cmd+Shift+P) and type “Copilot”. Look for a command like “GitHub Copilot: Enable/Disable”. Make sure it’s enabled (it should be by default after installation).
At this point, GitHub Copilot is fully configured in your development environment. The next step is to actually use it in developing a TMF Open API application. We will now walk through writing code with Copilot’s assistance, focusing on a TMF Open API use case.
Writing TMF Open API Apps Using GitHub Copilot
Now for the fun part – using GitHub Copilot to help write an application that implements a TMF Open API. In this section, we’ll provide a step-by-step example of how you might develop a simple service using a TMF Open API (say, a Customer Management API) with Copilot’s assistance. The principles can be applied to any TMF API or indeed any standard API.
Scenario: Let’s assume we want to build a minimal Customer Management microservice that conforms to the TMF629 Customer Management API (version 5.0) – which manages customer records. We will implement a simple endpoint to retrieve customer information by ID, as defined in the TMF API spec. We’ll use Node.js with an Express framework for this example, but you could choose Python (FastAPI/Flask) or Java (Spring Boot) similarly. The emphasis is on how Copilot assists with the coding.
Step 1: Referring to TMF Open API GitHub API specifications
Before coding, ensure you have the TMF629 API specification open or accessible for reference. For example, the spec might say there’s a GET operation at /tmf-api/customerManagement/v5/customer/{id} for retrieving a customer, and defines a Customer data model. If you have the YAML/JSON file, open it in a VS Code tab – this provides Copilot with a bunch of context (resource paths, field names, etc.). Copilot can use this textual context to inform its suggestions.
The spec files can be downloaded from below link (needs a TM Forum registration and login):
- Customer Management API REST API v5.0
- Open API Directory (Link for all API specifications)
Step 2: Set up the project scaffolding. Initialize a new Node.js project (e.g., run npm init -y for a Node project, and install Express by running npm install express). Then create a file index.js (or app.js). In that file, start with the basic Express server setup:
const express = require('express');
const app = express();
app.use(express.json());
// Start server on port 3000
app.listen(3000, () => {
console.log('TMF Customer API service is running on port 3000');
});
As you type the above, Copilot may autocomplete parts of it. For instance, after writing app.listen(3000, () => {, you might see it suggest a console.log line. It’s standard boilerplate, so nothing magical yet, but it confirms Copilot is active.
Step 3: Implement an API endpoint using Copilot.
Consider the TMF629 Customer Management API
Customer Management API TMF629-v5.0
Now, according to the TMF specification, the GET Customer by ID endpoint should be something like: GET https://host:port/tmf-api/customerManagement/v5/customer/{customerId} -> returns customer details.
Let’s write a handler for this. Start typing the Express route definition. For example:
// GET customer by ID
app.get('/tmf-api/customerManagement/v5/customer/:id', (req, res) => {
//
});
The moment you write the path string and arrow function, Copilot is likely to recognize this as a request handler and may suggest code inside. It has context from the route path (which is quite specific and likely uncommon except from the TMF spec) and the comment. Copilot might suggest something like: fetching the customer by ID from a database or returning a placeholder. Since we haven’t defined a database in this simple scenario, let’s see what it does. Often, for a new route, Copilot might guess you want to send a response. It could for example suggest:
// ... inside the handler:
const customerId = req.params.id;
// TODO: fetch customer from database (this is a Copilot suggestion comment)
res.status(200).json({ id: customerId, name: "Sample Customer" });
});
Of course, this is just an example of what Copilot might do. In practice Copilot may complete the code differently. The key is that Copilot can help stub out the logic. If it doesn’t automatically fill it, you can nudge it by writing a comment or function description inside the handler, such as:
// Find customer by ID and return as JSON
After writing that comment, pause and see if Copilot suggests a code block that finds a customer. If we had more context (like a Customer array or database connector imported), it might try to use it. For now, you can accept a basic implementation (like returning a dummy object as above).
Accepting the suggestion, our route becomes:
// GET customer by ID
app.get('/tmf-api/customerManagement/v5/customer/:id', (req, res) => {
const customerId = req.params.id;
// For demo, return a dummy customer object
res.json({ id: customerId, name: "John Doe", status: "ACTIVE" });
});
Here we assumed Copilot suggested returning an object with some fields. If the TMF spec defines fields for a Customer (e.g., name, status), and especially if the spec file is open in another tab, Copilot might use actual field names from the spec in its suggestion because it “saw” them in the YAML. This is a huge win: it helps ensure your code uses correct field names and structure as per the standard. For instance, if the spec says a Customer resource has id, name, status, Copilot might include those. Always verify against the spec, but it often aligns.
You continue this way for other operations (PUT/PATCH to update a customer, etc.), each time leveraging Copilot to write the initial code which you then adjust. Copilot can also help with non-HTTP logic: for example, if you need a function to validate an email address, just write the function signature and a comment, and it will likely fill it in (because such patterns are common in its training).
Step 5: Use Copilot for documentation and examples. Copilot can even assist in writing documentation-like content or tests for your API. For instance, you could create a README.md for your project.
Step 6: Iterate and refine with Copilot Chat (if available). GitHub Copilot includes a Chat mode (Copilot Chat) in VS Code, which acts like an assistant you can converse with in natural language. If you have Copilot Chat enabled, you can ask it things like “How do I implement pagination in this API according to TMF guidelines?” or “Suggest improvements for error handling in my code”. The chat can analyze your code base and provide guidance or even write code snippets to apply.
GitHub Copilot provides the capability to choose your own model (e.g. GPT-4.1, GPT-4o, GPT-5 or Claude 3.5 Sonnet, etc.). This provides additional flexibility to Telco developers building solutions on TM Forum (TMF) Open APIs. This flexibility means developers aren’t limited to one generic AI assistant – they can select the model best suited to each coding task, whether for rapid code suggestions or complex problem-solving.
Step 7: Test and validate against the TMF spec. Once you have your endpoints coded with Copilot’s help, it’s crucial to test them against the TMF specification to ensure correctness. Use tools like Postman or curl to call your API endpoints. For instance, GET http://localhost:3000/tmf-api/customerManagement/v5/customer/123 should return either a dummy customer (if using in-memory data as above) or a 404 if not found, as per spec expectations. Compare response structures to the TMF API definition. If something is missing or named incorrectly (say Copilot used customerName but spec expects name), adjust your code accordingly. Copilot is not guaranteed to produce 100% correct or updated spec implementations – it provides a helpful draft, but you are responsible for aligning it exactly with TMF’s definitions.
During testing, you might encounter bugs or mismatches. This is another point where Copilot can assist: if you get an error or exception, you can paste it into Copilot Chat or as a comment and prompt Copilot to help fix it. For example, if you see your server crashes on a null reference, you can write a comment // Copilot: fix null reference in customer lookup near the code, and it might suggest a null-check.
Best Practices and Tips for Using Copilot with TMF Open APIs
To use GitHub Copilot efficiently for TMF Open API development, follow these key practices:
Apply Copilot for Repetitive Tasks: When implementing endpoints with similar logic (e.g., CRUD operations), use an initial example as a template. Copilot will recognise patterns and help adapt code for new entities.
Prompt Clearly and Iterate: Refine prompts to get better suggestions; add specifics in comments for improved results. If output isn't right, adjust your instructions for more detail.
Verify Against TMF Standards: Copilot's knowledge may not reflect the latest TMF specs. Double-check generated code against official documentation and provide context from newer specs when necessary.
Incorporate Security and Quality Checks: Always validate Copilot’s code for security and proper input handling. Use Copilot Chat for advice on improving validation and ensure you meet industry standards (e.g., OAuth).
Learn From Suggestions: Use Copilot to expand your skills, especially if you're new to a language or framework, but confirm that its examples suit your use case.
Don’t Over Rely on Automation: Copilot is best for boilerplate and common patterns; customise business logic and architecture-specific code yourself.
Keep Relevant Files Open: Copilot works best with focused context. Close unrelated files to improve suggestion quality.
Update Copilot Regularly: Keep your extension up-to-date and try different AI models for improved performance.
Following these principles will help make Copilot a productive partner in TMF Open API projects, offering speed while maintaining adherence to standards.
CSPs Leveraging GitHub Copilot
Multiple Telco customers across the globe have adopted GitHub Copilot and have achieved a significant boost in their developer productivity.
In particular, Proximus has achieved below productivity benefits by adopting GitHub Copilot in their Network IT function.
|
Code |
Test | ||||
|
Write Code |
Refactor |
Code Documentation |
Code Review |
Code Compliance |
Unit Test |
|
↑20-30% |
↑25-35% |
↑80 - 90% |
↑5-10% |
↑40 – 50% |
↑20-30% |
More details here: (2) Transforming Telecommunications with Generative AI: Proximus and TCS's GitHub Copilot Journey | LinkedIn
Other Telco Customer Stories
NOS empowers developer collaboration and innovation on GitHub | Microsoft Customer Stories
With GitHub, Canadian company TELUS aims to bring ‘focus, flow and joy’ to developers - Source
https://github.com/customer-stories/telus
What's Next?
Agent mode to autonomously complete tasks
Telco developers can boost productivity with GitHub Copilot’s Agent Mode, which acts as an autonomous coding partner. Agent Mode handles multi-step coding tasks—such as implementing TMF Open API flows—reducing manual effort and speeding up feature delivery. It automates complex processes like file selection, testing, and error correction, allowing developers to concentrate on higher-level design while routine tasks run in the background.
Write and execute test plans
GitHub Copilot Chat can quickly generate test plans. Acting as an AI pair-tester, Copilot produces unit tests from your existing code or specs. Telco developers can highlight a method, request test generation, and instantly receive comprehensive test suggestions for different scenarios.
Conclusion
Setting up GitHub Copilot for TMF Open API projects streamlines productivity. This blog covered Copilot’s setup, its application to TMF-compliant services, and provided best practices like offering context and reviewing AI-generated code. Copilot speeds up development by handling boilerplate and suggesting standard patterns so you can focus on business logic. It fits seamlessly into your workflow, producing helpful suggestions when guided with clear specs and prompts. Developers report saving time and reducing complexity.
Still, Copilot shouldn’t replace understanding TMF APIs or good engineering habits; always verify code accuracy. Combining your expertise with Copilot’s capabilities leads to efficient, high-quality implementations. Explore features like Copilot CLI and keep up-to-date via TM Forum resources, including the Open API Table and community forums.
With the right setup and practices, you’re ready to develop robust TMF Open API apps, leveraging AI for faster results.
Microsoft